• Journal of Korean Society of Forest Science
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• v.88 no.1
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• pp.73-85
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• 1999

This study was conducted to reveal the characteristics of the early growth by locality for Korean white pine planted in Gapyung and Kwangju, Kyunggi-Do and Youngdong, Choongchungbuk-Do. The effects of local climatic conditions as one of environmental factors on the growth were also analyzed. For this, several stand variables such as number of trees survived, mean DBH, mean height, basal area per hectare, and volume per hectare by stand age were measured and summarized for each locality. Based on these statistics, periodic annual increments for 8 years from stand age 10 to 18 were calculated for each of stand variables. A topoclimatological technique, for the estimation of local climatic conditions, which makes use of empirical relationships between the topography and the weather in study areas was applied to produce reasonable estimates of monthly mean, maximum, minimum temperatures, relative humidity, precipitation, and hours of sunshine over remote land area where routine observations are rare. From these monthly estimates, 17 weather variables such as warmth index, coldness index, index of aridity etc. which affect the tree growth, were computed for each locality. The periodic annual increments were then correlated with and regressed on the weather variables to examine effects of local weather conditions on the growth. Gapyung area provided the best conditions for the growth of Korean white pine in the early stage and Kwangju area ranked second. On the other hand, the growth pattern in Youngdong ranked last overall as expected. It is also found that the local growth patterns of Korean white pine in juvenile stage were affected by typical weather conditions. The conditions such as low temperature, high relative humidity, and large amount of precipitation provide favorable environment for the growth of Korean white pine. Especially, the diameter growth, basal area growth, and volume growth are mainly influenced by the amount of precipitation. However, it is proved that the height growth is affected by both the precipitation and temperature.

• Korean Journal of Remote Sensing
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• v.14 no.1
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• pp.53-68
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• 1998

Observation of hydrometeors' behavior in the atmosphere is important to understand weather and climate. By conventional observations, we can get the distribution of water vapor at limited number of points on the earth. In this study, the precipitable water has been estimated from the split window channel data on GMS-5 based upon the technique developed by Chesters et al.(1983). To retrieve the precipitable water, water vapor absorption parameter depending on filter function of sensor has been derived using the regression analysis between the split window channel data and the radiosonde data observed at Osan, Pohang, Kwangiu and Cheju staions for 4 months. The air temperature of 700 hPa from the Global Spectral Model of Korea Meteorological Administration (GSM/KMA) has been used as mean air temperature for single layer radiation model. The retrieved precipitable water for the period from August 1996 through December 1996 are compared to radiosonde data. It is shown that the root mean square differences between radiosonde observations and the GMS-5 retrievals range from 0.65 g/$cm^2$ to 1.09 g/$cm^2$ with correlation coefficient of 0.46 on hourly basis. The monthly distribution of precipitable water from GMS-5 shows almost good representation in large scale. Precipitable water is produced 4 times a day at Korea Meteorological Administration in the form of grid point data with 0.5 degree lat./lon. resolution. The data can be used in the objective analysis for numerical weather prediction and to increase the accuracy of humidity analysis especially under clear sky condition. And also, the data is a useful complement to existing data set for climatological research. But it is necessary to get higher correlation between radiosonde observations and the GMS-5 retrievals for operational applications.

• Korean Journal of Remote Sensing
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• v.38 no.5_2
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• pp.747-763
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• 2022

Ocean salinity affects ocean circulation on a global scale and low salinity water around coastal areas often has an impact on aquaculture and fisheries. Microwave satellite sensors (e.g., Soil Moisture Active Passive [SMAP]) have provided sea surface salinity (SSS) based on the dielectric characteristics of water associated with SSS and sea surface temperature (SST). In this study, a Light Gradient Boosting Machine (LGBM)-based model for generating high resolution SSS from Geostationary Ocean Color Imager (GOCI) data was proposed, having machine learning-based improved SMAP SSS by Jang et al. (2022) as reference data (SMAP SSS (Jang)). Three schemes with different input variables were tested, and scheme 3 with all variables including Multi-scale Ultra-high Resolution SST yielded the best performance (coefficient of determination = 0.60, root mean square error = 0.91 psu). The proposed LGBM-based GOCI SSS had a similar spatiotemporal pattern with SMAP SSS (Jang), with much higher spatial resolution even in coastal areas, where SMAP SSS (Jang) was not available. In addition, when tested for the great flood occurred in Southern China in August 2020, GOCI SSS well simulated the spatial and temporal change of Changjiang Diluted Water. This research provided a potential that optical satellite data can be used to generate high resolution SSS associated with the improved microwave-based SSS especially in coastal areas.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.6
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• pp.882-889
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• 2022

In this study, to understand the factors influencing the flow change the Tsushima Warm Current (TWC), the correlation between the volume transport the TWC, El Niño Southern Oscillation (ENSO), and Pacific Decadal Oscillation (PDO) was analyzed. A calculation of the monthly volume transport of TWC for 25 years (1993-2018) revealed that the seasonal fluctuation cycle was the largest in summer and smallest in winter. Power spectrum analysis to determine the periodicity of the TWC volume transport, Oceanic Niño Undex (ONI), and PDO indicated that the TWC volume transport peaked at a one year cycle, but ONI and PDO showed no clear cycle. Further, to understand the correlation between the TWC transport volume and ONI and PDO, the coherence estimation method was used for analysis. The coherence of ONI and PDO had a high mutual contribution in long-period fluctuations of three years or more but had low mutual contribution in short-period fluctuations within one year. However, the coherence value between the two factors of the TWC volume transport and PDO was 0.7 in the 0.8-1.2 year cycle, which had a high mutual contribution. Meanwhile, the TWC volume transport and PDO have an inverse correlation between period I (1993-2002) and period III (2010-2018). When the TWC maximum transport volume (2.2 Sv or more) was high, the PDO index showed a negative value below -1.0, and the PDO index showed a positive value when the TWC maximum transport volume was (below 2.2 Sv). Therefore, using long-term PDO index data, changes in the TWC transport volume and water temperature in the East Sea coastal area could be predicted.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.329-339
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• 2021

Soybeans (Glycine max), one of major upland crops, require precise management of environmental conditions, such as temperature, water, and soil, during cultivation since they are sensitive to environmental changes. Application of spectral technologies that measure the physiological state of crops remotely has great potential for improving quality and productivity of the soybean by estimating yields, physiological stresses, and diseases. In this study, we developed and validated a soybean growth prediction model using multispectral imagery. We conducted a linear regression analysis between vegetation indices and soybean growth data (fresh weight and LAI) obtained at Miryang fields. The linear regression model was validated at Goesan fields. It was found that the model based on green ratio vegetation index (GRVI) had the greatest performance in prediction of fresh weight at the calibration stage (R²=0.74, RMSE=246 g/m², RE=34.2%). In the validation stage, RMSE and RE of the model were 392 g/m² and 32%, respectively. The errors of the model differed by cropping system, For example, RMSE and RE of model in single crop fields were 315 g/m² and 26%, respectively. On the other hand, the model had greater values of RMSE (381 g/m²) and RE (31%) in double crop fields. As a result of developing models for predicting a fresh weight into two years (2018+2020) with similar accumulated temperature (AT) in three years and a single year (2019) that was different from that AT, the prediction performance of a single year model was better than a two years model. Consequently, compared with those models divided by AT and a three years model, RMSE of a single crop fields were improved by about 29.1%. However, those of double crop fields decreased by about 19.6%. When environmental factors are used along with, spectral data, the reliability of soybean growth prediction can be achieved various environmental conditions.

• Korean Journal of Agricultural and Forest Meteorology
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• v.19 no.3
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• pp.153-163
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• 2017

The objective of this study is to enhance the model's speed of estimating weather variables (e.g., minimum/maximum temperature, sunshine hour, PRISM (Parameter-elevation Regression on Independent Slopes Model) based precipitation), which are applied to the Agrometeorological Early Warning System (http://www.agmet.kr). The current process of weather estimation is operated on high-performance multi-core CPUs that have 8 physical cores and 16 logical threads. Nonetheless, the server is not even dedicated to the handling of a single county, indicating that very high overhead is involved in calculating the 10 counties of the Seomjin River Basin. In order to reduce such overhead, several cache and parallelization techniques were used to measure the performance and to check the applicability. Results are as follows: (1) for simple calculations such as Growing Degree Days accumulation, the time required for Input and Output (I/O) is significantly greater than that for calculation, suggesting the need of a technique which reduces disk I/O bottlenecks; (2) when there are many I/O, it is advantageous to distribute them on several servers. However, each server must have a cache for input data so that it does not compete for the same resource; and (3) GPU-based parallel processing method is most suitable for models such as PRISM with large computation loads.

• Journal of the Korean Society for Marine Environment & Energy
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• v.17 no.4
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• pp.306-317
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• 2014

This study has been executed to understand the additional and removal processes of nutrients in the Saemangeum Salt-water Lake, and discussed with other monthly-collected environmental parameters such as water temperature, salinity, dissolved oxygen, suspended solids, and Chl-a from 2008 to 2010. $NO_3$-N, TP, $PO_4$-P, and DISi showed the removal processes along with the salinity gradients at the surface water of the lake, whereas $NO_2$-N, $NH_4$-N, and Chl-a showed addition trend. In the bottom water all water quality parameters except $NO_3$-N appeared addition processes indicating evidence of continuous nutrients suppliance into the bottom layer. The mixing modelling approach revealed that the biogeochemical processes in the lake consume $NO_3$-N and consequently added $NH_4$-N and $PO_4$-P to the bottom water during the summer seasons. The $NH_4$-N and $PO_4$-P appeared strong increase at the bottom water of the river-side of the lake and strong concentration gradient difference of dissolved oxygen also appeared in the same time. DISi exhibited continuous seasonal supply from spring to summer. Internal addition of $NH_4$-N and $PO_4$-P in the river-side of the lake were much higher than the dike-side, while the increase of DISi showed similar level both the dike and river sides. The temporal distribution of benthic flux for DISi indicates that addition of nutrients in the bottom water was strongly affected by other sources, for example, submarine ground-water discharge (SGD) through bottom sediment.

• Korean Journal of Remote Sensing
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• v.30 no.4
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• pp.481-491
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• 2014

Blue-ice area is a glacial ice field in ice sheet, ice shelf and glaciers where snow ablation and sublimation is larger than snowfall. As the blue-ice area has large influences on the meteorite concentration mechanism and ice mass balance, it is required to quantify the concentration of blue-ice. We analyzed spectral reflectance characteristics of blue-ice, snow and cloud by using MODIS images obtained over blue-ice areas in McMurdo Dry Valleys, East Antarctica, from 2007 to 2012. We then developed Normalized Difference Blue-ice Index (NDBI) algorithm which quantifies the concentration of blue-ice. Snow and cloud have a high reflectance in visible and near-infrared (NIR) bands. Reflectance of blue-ice is high in blue band, while that lowers in the NIR band. NDBI is calculated by dividing the difference of reflectance in the blue and NIR bands by the sum of reflectances in the two bands so that NDBI = (Blue-NIR)/(Blue + NIR). NDBI calculated from the MODIS images showed that the blue-ice areas have values ranging from 0.2 to 0.5, depending on the exposure and concentration of blue-ice. It is obviously different from that of snow and cloud that has values less than 0.2 or rocks with negative values. The change of NDBI values in the blue-ice area has higher correlation with snow depth ($R^2=0.699$) than wind speed ($R^2=0.012$) or air temperature ($R^2=0.278$), all measured at a meteorological station installed in McMurdo Dry Valleys. As the snow depth increased, the NDBI value decreased, which suggests that snow depth can be estimated from NDBI values over blue-ice areas. The NDBI algorithm developed in this study will be useful for various polar research fields such as meteorite exploration, analysis of ice mass balance as well as the snow depth estimation.

• Journal of Soil and Groundwater Environment
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• v.13 no.5
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• pp.57-73
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• 2008

Nitrate concentrations were measured up to 49 mg/L (as $NO_3$-N) and 22% of the samples exceeded drinking water standard in shallow and bedrock groundwater of the northern Nonsan area. Nitrate concentrations showed a significant difference among land use groups. To predict nitrate concentration in groundwater, multiple regression analysis was carried out using hydrogeologic parameters of soil media, topography and land use which were categorized as several groups, well depth and altitude, and field parameters of temperature, pH, DO and EC. Hydrogeologic parameters were quantified as area proportions of each category within circular buffers centering at wells. Regression was performed to all the combination of variables and the most relevant model was selected based on adjusted coefficient of determination (Adj. $R^2$). Regression using hydrogelogic parameters with varying buffer radii show highest Adj. $R^2$ at 50m and 300m for shallow and bedrock groundwater, respectively. Shallow groundwater has higher Adj. $R^2$ than bedrock groundwater indicating higher susceptibility to hydrogeologic properties of surface environment near the well. Land use and soil media was major explanatory variables for shallow and bedrock groundwater, respectively and residential area was a major variable in both shallow and bedrock groundwater. Regression involving hydrogeologic parameters and field parameters showed that EC, paddy and pH were major variables in shallow groundwater whereas DO, EC and natural area were in bedrock groundwater. Field parameters have much higher explanatory power over the hydrogeologic parameters suggesting field parameters which are routinely measured can provide important information on each well in assessment of nitrate contamination. The most relevant buffer radii can be applied to estimation of travel time of contaminants in surface environment to wells.

• Journal of Conservation Science
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• v.20
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• pp.9-22
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• 2007

Three kinds of natural pesticides extracted from plants which are being sold in the Korean markets, were estimated effects on materials of art of museum. Tested samples were 1) silk fabrics : undyed, dyed(amur cork tree, gallut, gallut(alum post mordancy), gallut(copperas post mordancy), gardenia, turmeric, acorn, acorn(copperas post mordancy), gromwell, madder, madder(alum post mordancy), safflower, sappanwood, sappanwood(alum pre mordancy, post mordancy), indigo, indigo+amur cork tree, indigo+sappanwood) 2) cotton fabrics : undyed, dyed(amur cork tree, gallut, gallut(alum post mordancy), gardenia, acorn, acorn(copperas post mordancy), gromwell, madder, madder(alum post mordancy), safflower, sappanwood, sappanwood(alum pre mordancy, post mordancy), indigo, indigo+sappanwood) 3) undyed ramie fabric 4) Korean papers : undyed, dyed(sappanwood, indigo, gardenia, amur cork tree, safflower) 5) pigments : azurite, malachite, red lead, litharge, orpiment, hematite, iron oxide, cinnabar, vermilion, indigo, lake indigo, kaolin, lead white, oyster shell white 6) painted plates : azurite, malachite, red lead, litharge, orpiment, hematite, iron oxide, cinnabar, vermilion, indigo, lake indigo, kaolin, lead white, oyster shell white. Conditions of tests were that after samples were exposed to 10 times of promoted concentration for 9 months in relative humidity $55{\pm}1%$ and temperature $20{\pm}2^{\circ}C$, they were compared with standards. Items of estimation were color difference(${\Delta}E^*$) and tenacity. After exposure to pesticides, undyed silk cotton ramie fabrics and Korean papers were not nearly changed in their colors, but colors of most of dyed samples were clearly changed by pesticides except for partial samples(acorn- and madder-dyed fabrics etc, gardenia-dyed samples). Especially changes of colors of turmeric-dyed silk fabrics were most distinct. And colors of pigments and painted plates containing lead, copper, arsenic, mercury and vegetable pigments, were clearly changed. Tenacities of yams of undyed silk fabrics were not nearly changed and undyed cotton fabrics were a little reduced as compared with standards. But tenacities of yams of dyed silk and cotton fabrics were clearly reduced or increased as compared with standards. Especially, madder-dyed silk fabrics were increased 10% or more and indigo-dyed silk fabrics were reduced 10% or less in all pesticides. Also madder- and sappanwood(alum post mordancy)-dyed cotton fabrics were increased 10% or more in all pesticides.